Current Research on Leadership Development Trust, technology adoption, and insider threat

This paper I will first address the basics of online trust, what increases or decreases trust levels. Next I explore why some users choose to adopt certainly technologies, and the role trust plays in those technologies. This includes trust of users to information systems, and trust of users to other users using the information system. Finally, I discuss the relationship between trust and malicious insiders, as we soon discover organizations can be too trusting of their employees and they may abuse information available to them. Motivated by revenge or financial gain, trusted users may commit fraud, sabotage, or information theft.

Trust
First we discuss the basis of trust in a virtual environment, such as establishing trust between virtual teams and working groups. As we discussed in my last paper, Giddens argues that trust is a stabilizing characteristic to provide reassurance in an uncertain society. (Giddens, 1991) The core of this paper discusses how we come with trust in an online environment, and trust other users to behave in an appropriate manner.

Corritore’s Online Trust Model
Corritore, et al. proposes a model of online trust which exists as a construct of external factors and the perception of external factors. This model is built up from an understanding of previous trust models, both in online and offline trust relationships, and provides a definition of online trust, which proves helpful to understand the specific scope of this paper and its focus. Specifically, trust in an online environment is not trustworthiness, faith, cooperation, or credibility. All these are factors that may contribute to trust, but they are not trust in themselves. Rather, online trust is composed of risk, vulnerability, expectation, confidence, and no exploitation. (Corritore, Kracher, & Wiedenbeck, 2003) They state “Trust encompasses the perception that a person has vulnerabilities and that those vulnerabilities could be breached or capitalized on.”

Corritore, et al. specifically provides a definition of online trust as: “An attitude of confident expectation in an online situation of risk that one’s vulnerabilities will not be exploited.” (2003) They provide an analogy between online and offline trust by creating four dimensions of online trust:
Generality exists as the trustor shifts from general to specific trust. General trust exists when you have overall trust in a person, thing, or website, while specific trust is reliant on a specific characteristic of the trustee, such as a specialist physician or a government website.
Kinds of trust include “slow and swift” trust and “cognitive and emotional” trust. An online example of cognitive and emotional trust is a website that appeals to both the user aesthetically and provides valuable information or services.
Degrees of trust are a progression in depth of trust, starting out weak and growing stronger as degrees of trust progress. These include Basic Trust, Guarded Trust, and Extended Trust.
Stages of trust describe a growth of trust, including Deterrence Based, Knowledge Based, and Shared Identification Based trust.
Each of these dimensions includes factors that differentiate between online and offline trust, but allows the research to draw conclusions from either. (Corritore, Kracher, & Wiedenbeck, 2003)

Quite a bit of research has been created in the realm of Human Computer Interactions (HCI), from website design to error messages, and many relate to establishing trust with a user. Errors in a website, just as by a company or a person, over time will degrade trust with the user. Interestingly, multiple small errors over time may have more of an impact to degrade trust rather than a few large errors. Corritore calls these “Trust Cues”, and are used to build trust factors both online and offline, crossing the boundary between domains. From website design to recommender systems, typographical errors to transaction ratings, a multitude of trust cues affect the creation or destruction of trust, to encourage or discourage the trustor from trusting. (Corritore, Kracher, & Wiedenbeck, 2003)

These theories are summarized in a model of on-line trust, which is made up of two factors of trust, external and perceived. This is described in figure 1, which shows the relationship and generation of online trust. External factors include aspects of the environment, psychological and physical, which contribute to trust. In the online model, this may be website design, features, accuracy, and seals of approval. However, online trust is a perceived experience, and perceived factors in this model are website credibility, ease of use, and risk. (Corritore, Kracher, & Wiedenbeck, 2003)

Credibility and the perception of credibility has four components: Honesty, Expertise, Predictability, and Reputation. Corritore, et al. cites researchers that described honesty as synonymous with trustworthy, and expertise is competency or knowledge. Predictability is related to credibility, that a website will behave as expected. Reputation is also related to credibility, in the factor of a website’s past performance. (Corritore, Kracher, & Wiedenbeck, 2003)

Ease of Use describes how well users can achieve their goals while using a computer, as a mechanism to measure technology adoption. This will be discussed further as website usability is a core component of the Technology Acceptance Model (TAM) (Davis, 1989). In addition, one of the factors contributing to Robert Hanssen’s ability to commit espionage was difficulty using security mechanisms available in the FBI’s Automated Case system. (Band et al., 2006) Corritore relates Ease of Use to TAM in the argument that a website that is easy to navigate and find the information needed instills a sense of trust in the user, and satisfies the user with their online experience. The relationship of Ease of Use to the Technology Acceptance Model applies directly to the relationship between insider threat and trust. (Corritore, Kracher, & Wiedenbeck, 2003)

Risk, both in online and offline dimensions, is the likelihood of an undesirable outcome. A user’s perception of risk is closely linked to their trust. For example, a person buying a large ticket item online for the first time may feel they have little control over the transaction. Komiak & Benbasat argue that while consumers may not be fully aware of all the unknown risks, they have an “awareness of the unknown” that increases their perceived risk. (2004) However, Corritore, et al. argues their level of control is the same as a person who makes purchases all day long online, but their level of perceived risk is much lower. (2003) An exploration of perceived risk will be discussed later in technology adoption and trust, and insider threat and the trust trap.

Chopra and Wallace Online Trust Framework
To enable a strong discussion of trust in information systems, Chopra and Wallace propose a framework to evaluate trust in various domains in electronic environments. The four electronic environments include:
Information
Information systems
e-commerce
Online Relationships

During my last paper I discussed how trust is a human activity, from interpersonal trust to team trust to societal trust. Chopra and Wallace extend this discussion by addressing the difference between trust in a person and trust in an information system, in that information systems can not possess the qualities necessary of a social actor to trust. Trust in its nature requires an inherent quality of transformation due to influence on attitude and behavior, which a computer can not perform. (Chopra & Wallace, 2003)

Their model of trust is captured in Figure 2, which is a sliding scale of interpersonal relationships, from least personal on the left to more personal on the right. Important to note is how the scale shifts from trusting technology to trusting people through technology.

Trust in Technology
Trust in technology follows an interpersonal model of trust. In this case the trustee, or item being trusted, is a web page or electronic document. The information is trusted if it is believed to be reliable, and the trustor enters the relationship willingly, meaning they can accept or reject the information on the document.

Chopra and Wallace (2003) propose trust in information systems has two perspectives, interpersonal trust for specific systems, and societal trust for large networks, such as enterprise information systems. This follows the distinction I make in my last paper, where Eisenstadt, Luhmann, and Pettit discuss interpersonal trust, while Fukuyama, Gibson, Seligman and Urban discuss societal trust. Chopra and Wallace also make the distinction that trust in information is not the same type of trust as interpersonal trust, but a trust in the “proper functioning of computer hardware and software”. (Chopra & Wallace, 2003, p. 7) This is the foundation of Trusted Computing, and is an important distinction between Trusted Computing and interpersonal trust using information systems.

Trust in People
Trust in electronic commerce shifts the discussion closer to humanistic trust, where the trustee is now a person or organization, rather than an information system. In this case an individual’s confidence is that a transaction will be fulfilled appropriately. A number of mechanisms exist to increase the trust in electronic commerce, such as history, buyer and seller rating systems, branding, and predictability.

Finally Chopra and Wallace (2003) identify trust in online relationships. This type of trust closely follows the interpersonal model of trust. (Chopra & Wallace, 2003, p. 8) This situation may be a person engaged in a chat room, bulletin board, email, or other electronic communication resource for sharing information. The element of confidence is the other party will maintain the quality of the relationship. Cognitive trust is influenced by their credentials, while affective trust is created through an emotional bond.

Confidence in an online relationship derives from the other party’s intelligence, and their positive intentions are derived from their actions, such as the propensity to commit fraud, espionage, or mishandle the information. This relates directly to insider threats, discussed later in this paper. Ethics, predictability, dependability, and confidentially are summarily addressed. This definition of confidence is the same we used to define trust earlier. (Corritore, Kracher, & Wiedenbeck, 2003)

The propensity for an individual to trust an online relationship is driven by their technical savvy, and their disposition to trust. Trust in online relationships grow in a similar manner to real-world relationships, where it grows stronger based on previous interactions. Bonding occurs as the relationship evolves into friendship or romance. This follows to the Technology Acceptance Model, discussed later in this paper, where users with more comfort in technology are more likely to adopt technology. (Hsi-Peng, Chin-Lung, & Hsiu-Ying, 2005)

Chopra and Wallace (2003) conclude their discussion with a comprehensive framework. Their seven descriptions of trust are Nature, Elements, Preconditions, Dimensions, Trustworthiness, Influences, and Processes. Specific to our discussion of online trust, this framework demonstrates online relationship models closely follow the real-world trust relationship models. The context of trust is derived from the situation, the societal role of trust comes from introductions and referrals, and interpersonal trust relies on confidence and credentials.